The shift to digital broadcasting has improved the ability of content providers to determine the viewing behavior of their subscribers and other end users. Data received through digital converters, or set top boxes (STBs), can be collected and compared with a programmed schedule of broadcast content in order to estimate which programs are being viewed. The resulting viewing data can be communicated to a content provider, advertisers, and other interested parties to indicate when a particular group of subscribers has tuned to a particular piece of content.
With the advent of new distribution channels and flexible programming via which content providers are able to present content, however, it has become increasingly difficult using traditional techniques to determine the number of viewers viewing particular content and the impact of advertisements shown during that particular content. Although digital viewing data can be analyzed against regularly scheduled programming in which both program and advertisement times are scheduled, such traditional techniques fail for other types of programming. For example, local television stations will sometimes deviate from a programmed schedule of broadcasts, thereby making it difficult to assess which content is being viewed at which time. As another example, live programming will often have unpredictable schedules, such as sporting events which vary in length or important news events which pre-empt regularly-scheduled programming. Live programming therefore often results in inconsistent commercial breaks, length of programming, and start times for subsequent programming presented by a content provider. As yet another example, the use of digital video recorders (DVRs) allows viewers to watch recorded and/or streamed content on their own schedule. Accordingly, there is a need to improve the ability to assess a number of content viewers, particularly for content presented by content providers in a non-scheduled fashion.